Integration of transfer function model and back propagation neural network for forecasting storm sewer flow in Taipei metropolis

Typhoons and storms have often brought heavy rainfalls and induced floods that have frequently caused severe damage and loss of life in Taiwan. Our ability to predict sewer discharge and forecast floods in advance during storm seasons plays an important role in flood warning and flood hazard mitigation. In this paper, we develop an integrated model (TFMBPN) for forecasting sewer discharge that combines two traditional models: a transfer function model and a back propagation neural network. We evaluated the integrated model and the two traditional models by applying them to a sewer system of Taipei metropolis during three past typhoon events (NARI, SINLAKU, and NAKR). The performances of the models were evaluated by using predictions of a total of 6 h of sewer flow stages, and six different evaluation indices of the predictions. Finally, an overall performance index was determined to assess the overall performance of each model. Based on these evaluation indices, our analysis shows that TFMBNP yields accurate results that surpass the two traditional models. Thus, TFMBNP appears to be a promising tool for flood forecasting for the Taipei metropolis sewer system. For publication in Stochastic Environmental Research and Risk Analysis.     

Physical criteria for distinguishing sandy tsunami and storm deposits using modern examples

Modern subaerial sand beds deposited by major tsunamis and hurricanes were compared at trench, transect, and sub-regional spatial scales to evaluate which attributes are most useful for distinguishing the two types of deposits. Physical criteria that may be diagnostic include: sediment composition, textures and grading, types and organization of stratification, thickness, geometry, and landscape conformity.

Published reports of Pacific Ocean tsunami impacts and our field observations suggest that sandy tsunami deposits are generally < 25 cm thick, extend hundreds of meters inland from the beach, and fill microtopography but generally conform to the antecedent landscape. They commonly are a single homogeneous bed that is normally graded overall, or that consists of only a few thin layers. Mud intraclasts and mud laminae within the deposit are strong evidence of tsunami deposition. Twig orientation or other indicators of return flow during bed aggradation are also diagnostic of tsunami deposits. Sandy storm deposits tend to be > 30 cm thick, generally extend < 300 m from the beach, and will not advance beyond the antecedent macrotopography they are able to fill. They typically are composed of numerous subhorizontal planar laminae organized into multiple laminasets that are normally or inversely graded, they do not contain internal mud laminae and rarely contain mud intraclasts. Application of these distinguishing characteristics depends on their preservation potential and any deposit modifications that accompany burial.

The distinctions between tsunami and storm deposits are related to differences in the hydrodynamics and sediment-sorting processes during transport. Tsunami deposition results from a few high-velocity, long-period waves that entrain sediment from the shoreface, beach, and landward erosion zone. Tsunamis can have flow depths greater than 10 m, transport sediment primarily in suspension, and distribute the load over a broad region where sediment falls out of suspension when flow decelerates. In contrast, storm inundation generally is gradual and prolonged, consisting of many waves that erode beaches and dunes with no significant overland return flow until after the main flooding. Storm flow depths are commonly < 3 m, sediment is transported primarily as bed load by traction, and the load is deposited within a zone relatively close to the beach.     

Identification of tsunami deposits considering the tsunami waveform: An example of subaqueous tsunami deposits in Holocene shallow bay on southern Boso Peninsula, Central Japan

This study proposes a tsunami depositional model based on observations of emerged Holocene tsunami deposits in outcrops located in eastern Japan. The model is also applicable to the identification of other deposits, such as those laid down by storms. The tsunami deposits described were formed in a small bay of 10–20-m water depth, and are mainly composed of sand and gravel. They show various sedimentary structures, including hummocky cross-stratification (HCS) and inverse and normal grading. Although, individually, the sedimentary structures are similar to those commonly found in storm deposits, the combination of vertical stacking in the tsunami deposits makes a unique pattern. This vertical stacking of internal structures is due to the waveform of the source tsunamis, reflecting: 1) extremely long wavelengths and wave period, and 2) temporal changes of wave sizes from the beginning to end of the tsunamis.

The tsunami deposits display many sub-layers with scoured and graded structures. Each sub-layer, especially in sandy facies, is characterized by HCS and inverse and normal grading that are the result of deposition from prolonged high-energy sediment flows. The vertical stack of sub-layers shows incremental deposition from the repeated sediment flows. Mud drapes cover the sub-layers and indicate the existence of flow-velocity stagnant stages between each sediment flow. Current reversals within the sub-layers indicate the repeated occurrence of the up- and return-flows.

The tsunami deposits are vertically divided into four depositional units, Tna to Tnd in ascending order, reflecting the temporal change of wave sizes in the tsunami wave trains. Unit Tna is relatively fine-grained and indicative of small tsunami waves during the early stage of the tsunami. Unit Tnb is a protruding coarse-grained and thickest-stratified division and is the result of a relatively large wave group during the middle stage of the tsunami. Unit Tnc is a fine alternation of thin sand sheets and mud drapes, deposited from waning waves during the later stage of the tsunami. Unit Tnd is deposited during the final stage of the tsunami and is composed mainly of suspension fallout. Cyclic build up of these sub-layers and depositional units cannot be explained by storm waves with short wave periods of several to ten seconds common in small bays.     

2004年初春武汉机场临近的两次强雷暴天气过程分析

使用常规地面和高空原始报文资料,采用最优插值法,对2004年4月29日出现在武汉天河机场临近的两次强雷暴天气过程进行了客观诊断分析。结果表明:两次强雷暴天气,前一次为典型的飑线天气过程,后一次为超级雷暴单体天气过程;高空槽、冷锋、中尺度低值系统是当天两次强雷暴天气的触发机制;低空深厚湿层(水汽丰富)、高低空存在急流强风带对当日飑线天气的形成和发展较为有利,强的不稳定层结、强的环境风垂直切变以及上层干、下层湿的湿度层结对当天超级雷暴单体的形成和发展十分有利。     

北太平洋风暴轴异常变化特征及其与纬向风场的关系研究

摘要本文通过对300 hPa5、00 hPa和850 hPa的北太平洋风暴轴(PST)的异常研究,分别提取出两个主异常模态进行比较。分析表明在三层的第一主模态都主要对应有PST异常的准10 a的周期变化;而对300 hPa和500 hPa的第二主模态,以及850 hPa的第三模态,对应有更长时间的趋势变化。进一步通过相关的分析,说明PST的异常从低层到高层的变化存在一定的一致性。通过PST与纬向风场在300 hPa的相关分析发现,两个模态与纬向风场的异常在空间上都呈同位相的分布,说明高层纬向风场异常与PST发展可能存在一种互相反馈的作用。进一步通过斜压增长率和水平两维的E-P通量矢的合成分析发现,这种反馈作用,无论从纬向风场异常所产生的环境斜压增长条件的改变,还是从平均动能与扰动动能的转化关系,都是存在的。     

"龙王"(LONGWANG)台风过程湿位涡的诊断分析

本文应用MM5V3中尺度数值模式对0519号台风“龙王”过程进行了数值模拟,利用模拟结果计算了台风过程湿位涡(Moist Potential Vorticity,MPV)的演变,从湿位涡的角度研究了台风过程大暴雨的产生机制。结果表明:倾斜涡度发展是“龙王”台风在福建沿海产生大暴雨的重要机制之一,湿位涡能够对暴雨落区的预报有较强的指示性作用,暴雨产生在θse线陡立的对流层中低层MPV1等值线密集带中零线附近,对流层中高层的MPV2负值区可以作为暖湿气流或涡旋活动的示踪;另外,对流层中高层中高纬度冷空气扩散南下与台风的东南暖湿空气在福建沿海交汇,加剧了气旋性涡度发展,对暴雨的发生发展也有巨大的作用。     

A real-time, event-triggered storm surge forecasting system for the state of North Carolina

A new real-time, event-triggered storm surge prediction system has been developed for the State of North Carolina to assist emergency managers, policy-makers and other government officials with evacuation planning, decision-making and resource deployment during tropical storm landfall and flood inundation events. The North Carolina Forecast System (NCFS) was designed and built to provide a rapid response assessment of hurricane threat, accomplished by driving a high-resolution, two-dimensional, depth-integrated version of the ADCIRC (Advanced Circulation) coastal ocean model with winds from a synthetic asymmetric gradient wind vortex. These parametric winds, calculated at exact finite-element mesh node locations and directly coupled to the ocean model at every time step, are generated from National Hurricane Center (NHC) forecast advisories the moment they are inserted into the real-time weather data stream, maximizing the number of hours of forecast utility. Tidal harmonic constituents are prescribed at the open water boundaries and applied as tidal potentials in the interior of the ocean model domain. A directional surface roughness parameterization that modulates the wind speed at a given location based on the types of land cover encountered upwind, a forest canopy sheltering effect, and a spatially varying distribution of Manning’s–n friction coefficient used for computing the bottom/channel bed friction are also included in the storm surge model. Comparisons of the simulated wind speeds and phases against their real meteorological counterparts, of model elevations against actual sea surface elevations measured by NOAA tide gauges along the NC coast, and of simulated depth-averaged current velocities against Acoustic Doppler Current Profiler (ADCP) data, indicate that this new system produces remarkably realistic predictions of winds and storm surge.     

Quantifying the storm erosion hazard for coastal planning

The quantity of coastline retreat resulting from storm erosion is one of the most important phenomena that needs to be accurately quantified to facilitate effective coastal management strategies. Historically, the volume of storm erosion (and coastline retreat) accommodated for coastal planning decisions has been directly linked to the storm (usually defined by considering wave height and duration only) with a certain pre-defined return period, known as a Synthetic Design Storm (SDS) (e.g. 1 in 100 year storm). The SDS method of estimating storm erosion volumes for coastal planning thus assumes that, for example, the 1 in 100 year storm event also results in a 1 in 100 year erosion event. This communication discusses the physical reality of this assumption and demonstrates the improved performance of a new method, based on Joint Probability Distributions (JPD) for estimating storm erosion volumes proposed by Callaghan et al. [Callaghan, D.P., Nielsen, P., Short, A.D. and Ranasinghe, R., 2008. Statistical simulation of wave climate and extreme beach erosion. Coastal Engineering, 55(5): 375–390] using one of the world's longest beach profile surveys from Sydney, Australia.     

Large-scale dune erosion tests to study the influence of wave periods

Large-scale physical model tests were performed to quantify the effects of the wave period on dune erosion. Attention was focussed on 2D cross-shore effects in a situation with sandy dunes and extreme water levels and wave conditions. Besides profile measurements, detailed measurements in time and space of water pressure, flow velocities and sediment concentrations were performed in the near near-shore area. It was concluded that a longer wave period leads to a larger dune erosion volume and to a larger landward retreat of the dune face. Tests with double-peaked wave spectra showed that the influence of the spectral shape on dune erosion was best represented by the T_m − 1,0 spectral mean wave period, better than the peak wave period, T_p. The effect of the wave period on dune erosion was implemented in a dune erosion prediction method that estimates erosion volumes during normative storm conditions for the Dutch coast. More details of the measurements and additional analyses of physical processes are described in an accompanying paper by Van Thiel de Vries et al. [Van Thiel de Vries, J.S.M., van Gent, M.R.A., Reniers, A.J.H.M. and Walstra, D.J.R., submitted for publication. Analysis of dune erosion processes in large scale flume experiments, In this volume of Coastal Engineering.].     

Deterministic and ensemble storm surge prediction for Atlantic Canada with lead times of hours to ten days

Regional deterministic and ensemble surge prediction systems (RDSPS and RESPS respectively) are used to forecast sea levels off the east of Canada and northeast US. The surge models for the RDSPS and RESPS have grid spacings of 1/30° and 1/12° respectively. The models are driven by surface air pressure and 10 m winds generated by operational global deterministic and ensemble prediction systems that are run operationally by the Canadian Meteorological Centre. Surge forecasts are evaluated for the period 1 March, 2013 to 31 March 2014. Based on traditional statistics (e.g., standard deviation of the difference between observations and predictions) both systems are shown to have skill in forecasting surges six days into the future. It is shown however that skill exists beyond six days if allowance is made for errors in the timing of large surges. The usefulness of the RESPS is demonstrated for two positive surges (important for coastal flooding and erosion) and a negative surge (important for safe navigation in shallow water). It is shown that the RESPS can identify events not forecast by the RDSPS, and can also add useful additional information on the timing of the surge, an important consideration in tidally dominated waters. Several new types of display are used to illustrate the sort of information that can be generated by the RESPS to support the issuers of warnings of unusually high and low total water levels.